Otomoto
Feature Importances
Regression Stats
Individual Predictions
What if...
Feature Dependence
Decision Trees
Feature Importances
Model Summary
metric
Score
mean-squared-error
271040000.297
root-mean-squared-error
16463.293
mean-absolute-error
4398.489
mean-absolute-percentage-error
0.032
R-squared
0.985
Predicted vs Actual
Residuals
Plot vs feature
Are predictions and residuals correlated with features?
Individual Predictions
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Prediction
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Contributions Plot
How has each feature contributed to the prediction?
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Partial Dependence Plot
Contributions Table
How has each feature contributed to the prediction?
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What if...
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Prediction
input data incorrect
Feature Input
Adjust the feature values to change the prediction
Selected:
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1
109
110
3
49
121
123
113
61
68
24
47
58
64
31
27
8
38
55
71
90
100
86
87
101
29
25
128
124
52
93
83
103
88
126
18
106
117
17
2
115
108
56
82
59
114
40
62
73
120
22
5
46
89
97
35
42
84
99
10
23
127
33
34
94
98
77
45
125
30
112
44
81
111
122
39
6
119
43
11
105
41
85
9
19
51
50
48
53
67
92
21
32
130
132
129
4
36
95
78
70
134
0
104
14
107
116
28
75
60
57
118
7
80
12
69
79
13
76
37
26
16
74
65
72
54
66
133
131
15
20
91
96
102
63
Contributions Plot
How has each feature contributed to the prediction?
input data incorrect
Partial Dependence Plot
input data incorrect
Contributions Table
How has each feature contributed to the prediction?
input data incorrect
Feature Dependence
Shap Summary
Ordering features by shap value
Shap Dependence
Relationship between feature value and SHAP value
Decision Trees
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Decision Trees
Displaying individual decision trees inside xgboost model
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Decision path table
Decision path through decision tree
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